Abstract :This technique leads to faster convergence and provides reduced mean-squared error compared to the conventional fixed parameter LMS algorithm.

The algorithm has been tested for noise reduction and estimation in narrow-band FM signals corrupted by additive white Gaussian noise.

For the LMS algorithm in a white Gaussian noise environment. A general power decaying law has been studied, however, other time-varying laws could also be applicable.

The main idea is to set the convergence parameter to a large value in the initial state in order to speed up the algorithm convergence.



The modified algorithm has been tested for noise reduction and estimation in linear frequency-modulated (LFM) narrowband signals corrupted by additive white Gaussian noise.

Please find the following attachments"LMS Algorithm in the Presence of White Gaussian Noise seminar report/pdf download" here.....